• 한국융합학회논문지
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• 제5권4호
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• pp.137-146
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• 2014

본 연구는 3단계 지시따르기를 통한 수용언어촉진이 아스퍼거 아동의 반응시간에 미치는 효과에 대하여 알아보고자 실시되었다. 연구대상자는 3세 8개월 남아로, 반응이 느리고 지시따르기에 어려움을 보이는 특성을 보였다. 연구 설계는 행동간 복식기초선 설계법(multiple-baseline across behaviors)이었으며, 종속변인은 지시 후 아동의 반응에 걸리는 시간이었다. 연구결과 행동 1(손들기)의 경우 장면 1(자유놀이)의 기초선 반응시간 3회 평균 3.53초였던 것이 중재이후 평균 0.92초로 짧게 나타났다. 장면 2(생각놀이)의 기초선 반응시간 3회 평균 3.63초가 중재이후 평균 0.66초로 짧아졌다. 행동 2(지시수행하기)의 경우 장면 1(자유놀이) 6회 기초선 평균 3.12초에 나타난 반응이 중재 이후 평균 1.58초로 빠르게 나타났다. 장면 2(생각놀이)의 기초선 6회 평균 4.35초 였던 반응이 중재이후 평균 1.72초로 빠르게 나타났다. 행동 3(대답하기)의 경우 장면 1(자유놀이) 9회 기초선 평균 2.51초에 나타난 반응이 중재이후 평균 1.25초로 빠르게 나타났다. 장면 2(생각놀이)의 기초선 9회 평균 3.04초 였던 반응이 중재이후 평균 0.75초로 빠르게 나타났다. 본 연구를 통해 반응이 느린 아스퍼거 장애 아동의 수용언어 촉진에 3단계 지시따르기가 효과적임을 알 수 있었다.

• Journal of Chest Surgery
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• 제56권6호
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• pp.420-430
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• 2023

Background: This study provides an update to a landmark 2004 report describing demographics, training, and trends in adherence to thoracic surgery practice standards in Canada. Methods: An updated questionnaire was administered to all members of the Canadian Association of Thoracic Surgeons via email (n=142, compared to n=68 in 2004). Our report incorporates internal data from Ontario Health and the Canadian Partnership Against Cancer. Results: Forty-eight surgeons completed the survey (male, 70.8%; mean±standard deviation age, 50.3±9.3 years). This represents a 33.8% response rate, compared to 64.7% in 2004. Most surgeons (69%) served a patient population of over 1 million per center; 32%-34% reported an on-call ratio of 1:4-1:5 days, and the average weekly hours worked was 56.4±11.9. Greater access to dedicated geographic units per center (73% in 2021 vs. 53% in 2004) has improved thoracic-associated services and house staff, notably endoscopy units (100% vs. 91%), with 73% of respondents having access to both endobronchial and endoscopic ultrasound. Access to thoracic radiology has also improved, particularly regarding positron emission tomography scanners per center (76.9% vs. 13%). Annual case volumes for lung (255 vs. 128), esophageal (41 vs. 19), and mediastinal resections (30 vs. 13), along with hiatal hernia repair (45 vs. 20), have increased substantially despite reports of operating room availability and radiology as rate-limiting steps. Conclusion: This survey characterizes compliance with current practice standards, addressing the needs of thoracic surgeons across Canada. Over 85% of respondents were aware of the 2004 compliance paper, and 35% had applied for resources and equipment in response.

• Nutrition Research and Practice
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• 제16권6호
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• pp.801-812
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• 2022

BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.